Musculoskeletal Model Research Articles

The effect of simulated basketball game load on patellar tendon load during stop-jump movement

Patellar tendinopathy (PT) is frequently observed among basketball players, particularly in sports involving repetitive jumping movements. However, the overall impact of accumulated exercise load on the patellar tendon is still not fully comprehended. Therefore, the goal of this study is to examine how a simulated basketball game affects the biomechanics of stop-jump movements, specifically focusing on the effects on the patellar tendon. The kinematic and kinetic data were collected immediately after the warm-up and each phase of the simulated basketball game (P1, P2, P3, and P4). A musculoskeletal model was built to calculate patellar tendon force (PTF) and the key biomechanical metrics during the horizontal landing and vertical jumping phases were explored separately, followed by correlation analyses. Linear regression analyses were performed on variables strongly correlated with PTF. The accumulation of load led to significant differences (p < 0.05) in the angles, velocities, torques, work contributions, peak patellar tendon force (PTF), and anterior-posterior ground reaction force (APGRF) observed during the landing and vertical jump phases at the hip, knee, and ankle joints. PTF showed strong correlations with knee flexion angle, knee extension angular velocity, ankle plantarflexion angular velocity, and APGRF, with R2 values of 0.50, 0.58, 0.70, and 0.56, respectively. PTF significantly decreased in P3 and P4, possibly due to the subjects’ adaptation and adjustment of their stop-jump posture strategy after load accumulation, including reducing knee and hip flexion angles and decreasing the net knee extension moment.

Associations of back muscle endurance with occupational back muscle activity and spinal loading among subsistence farmers and office workers in Rwanda.

Over the course of the physical activity transition, machines have largely replaced skeletal muscle as the source of work for locomotion and other forms of occupational physical activity in industrial environments. To better characterize this transition and its effect on back muscles and the spine, we tested to what extent typical occupational activities of rural subsistence farmers demand higher magnitudes and increased variability of back muscle activity and spinal loading compared to occupational activities of urban office workers in Rwanda, and whether these differences were associated with back muscle endurance, the dominant risk factor for back pain. Using electromyography, inertial measurement units, and OpenSim musculoskeletal modeling, we measured back muscle activity and spinal loading continuously while participants performed occupational activities for one hour. We measured back muscle endurance using electromyography median frequency analysis. During occupational work, subsistence farmers activate their back muscles and load their spines at 390% higher magnitudes and with 193% greater variability than office workers. Partial correlations accounting for body mass show magnitude and variability response variables are positively associated with back muscle endurance (R = 0.39-0.90 [P < 0.001-0.210] and R = 0.54-0.72 [P = 0.007-0.071], respectively). Body mass is negatively correlated with back muscle endurance (R = -0.60, P = 0.031), suggesting higher back muscle endurance may be also partly attributable to having lower body mass. Because higher back muscle endurance is a major factor that prevents back pain, these results reinforce evidence that under-activating back muscles and under-loading spines at work increases vulnerability to back pain and may be an evolutionary mismatch. As sedentary occupations become more common, there is a need to study the extent to which occupational and leisure time physical activities that increase back muscle endurance helps prevent back pain.

Comparison of synergy extrapolation and static optimization for estimating multiple unmeasured muscle activations during walking

BackgroundCalibrated electromyography (EMG)-driven musculoskeletal models can provide insight into internal quantities (e.g., muscle forces) that are difficult or impossible to measure experimentally. However, the need for EMG data from all involved muscles presents a significant barrier to the widespread application of EMG-driven modeling methods. Synergy extrapolation (SynX) is a computational method that can estimate a single missing EMG signal with reasonable accuracy during the EMG-driven model calibration process, yet its performance in estimating a larger number of missing EMG signals remains unknown.MethodsThis study assessed the accuracy with which SynX can use eight measured EMG signals to estimate muscle activations and forces associated with eight missing EMG signals in the same leg during walking while simultaneously performing EMG-driven model calibration. Experimental gait data collected from two individuals post-stroke, including 16 channels of EMG data per leg, were used to calibrate an EMG-driven musculoskeletal model, providing “gold standard” muscle activations and forces for evaluation purposes. SynX was then used to predict the muscle activations and forces associated with the eight missing EMG signals while simultaneously calibrating EMG-driven model parameter values. Due to its widespread use, static optimization (SO) applied to a scaled generic musculoskeletal model was also utilized to estimate the same muscle activations and forces. Estimation accuracy for SynX and SO was evaluated using root mean square errors (RMSE) to quantify amplitude errors and correlation coefficient r values to quantify shape similarity, each calculated with respect to “gold standard” muscle activations and forces.ResultsOn average, compared to SO, SynX with simultaneous model calibration produced significantly more accurate amplitude and shape estimates for unmeasured muscle activations (RMSE 0.08 vs. 0.15, r value 0.55 vs. 0.12) and forces (RMSE 101.3 N vs. 174.4 N, r value 0.53 vs. 0.07). SynX yielded calibrated Hill-type muscle–tendon model parameter values for all muscles and activation dynamics model parameter values for measured muscles that were similar to “gold standard” calibrated model parameter values.ConclusionsThese findings suggest that SynX could make it possible to calibrate EMG-driven musculoskeletal models for all important lower-extremity muscles with as few as eight carefully chosen EMG signals and eventually contribute to the design of personalized rehabilitation and surgical interventions for mobility impairments.

Population-based in silico modeling of anatomical shape variation of the knee and its impact on joint loading in knee osteoarthritis.

Anatomical knee joint features and osteoarthritis (OA) severity are associated, however confirming causals link to altered knee loading is challenging. This study leverages statistical shape models (SSM) to investigate the relationship between joint shape/alignment and knee loading during gait in knee OA(KOA) patients to understand their contribution to elevated medial knee loading in OA. Musculoskeletal (MSK) models were created for the mean as well as the first eightSSM principal modes of variation (-3,-2,-1, +1, +2, +3 standard deviations for each mode) and used as input to a MSK modeling framework. Using an identical KOA gait pattern (i.e., joint kinematics and ground reaction forces), we ran simulations for each MSK model and evaluated medial compartment loading magnitude and contact distribution at the instant of first and second peak of knee joint loading. An increase in external rotation, posterior tibia translation and a decrease in medial joint space and medial femoral condylar size predisposed the medial compartment knee joint to overloading during gait. This was coupled with an anterior and medial shift in contact location with increasing external rotated tibial position and increasing posterior tibial translation with respect to the femur. Next, results also highlighted a posterior shift of the medial compartment loading location with decreasing medial joint space. This study provides important population-based insights on how knee shape and alignment predispose individuals with KOA to elevated medial compartmental knee loading. This information can be crucial in assessing the risk for medial KOA development and progression.

Effect of patient specificity on predicting knee cartilage degeneration in obese adults: Musculoskeletal finite-element modeling of data from the CAROT trial.

Obesity is a known risk factor for development of osteoarthritis (OA). Numerical tools like finite-element (FE) models combined with degenerative algorithms have been developed to understand the interplay between OA and obesity. Inthisstudy,we aimed to predict knee cartilage degeneration in a cohort of obese adults to investigate the importance of patient-specific information on degeneration predictions. We used a validated FE modeling approach and three different age-dependent functions (step-wise, exponential, and linear) to simulate cartilage degradation under overloading in the knee joint. Gait motion analysis and magnetic resonance imaging data from 115 obese individuals with knee OA were used for musculoskeletal and FE modeling. Cartilage degeneration predictions were contrasted with Kellgren-Lawrence (KL)and Boston-Leeds Osteoarthritis Knee Score (BLOKS) grades. The findings show that overall, the similarities between numerical predictions and clinical measures were better for the medial (average area under the curve(AUC) = 0.62) compared to the lateral compartment (average AUC = 0.52) of the knee. Classification results for KL grades, full patient-specific models and patient-specific geometry with generic gait data showed higher AUC values (AUC = 0.71 and AUC = 0.68, respectively) compared to generic geometry and patient-specific gait (AUC = 0.48). For BLOKS grades, AUC values for both full patient-specific models and for patient-specific geometry with generic gait locomotion were higher (AUC = 0.66 and AUC = 0.64, respectively) compared to when the generic geometry and patient-specific gait were used (AUC = 0.53). In summary, our study highlights the importance of considering individual information in knee OA prediction. Nevertheless, our findings suggest that personalized gait play a smaller role in the OA prediction and classification capacity than personalized joint geometry.

Lower limb joint loading during high-impact activities: implication for bone health.

Osteoporosis results in low-trauma fractures affecting millions globally, in particular elderly populations. Despite the inclusion of physical activity in fracture prevention strategies, the optimal bone-strengthening exercises remain uncertain, highlighting the need for a deeper understanding of lower limb joint loading dynamics across various exercise types and levels. This study examines lower limb joint loading during high-impact exercises across different intensities. A total of 40 healthy, active participants were recruited (mean ± SD: age of 40.3 ± 13.1yr; height 1.71 ± 0.08m; and mass 68.44 ± 11.67kg). Motion capture data and ground reaction forces of 6 different exercises: a self-selected level of walking, running, countermovement jump, squat jump, unilateral hopping, and bilateral hopping were collected for each participant. Joint reaction forces were estimated using lower body musculoskeletal models developed in OpenSim. Running and hopping increased joint forces compared to walking, notably at the hip (83% and 21%), knee (134% and 94%), and ankle (94% and 77%), while jump exercises reduced hip and ankle loading compared to walking (36% and 19%). Joint loading varied with exercise type and intensity, with running faster increasing forces on all joints, particularly at the hip. Sprinting increased forces at the hip but lowered knee and ankle forces. Higher jumps intensified forces on all joints, while faster hopping reduced forces. The wide variation of lower limb joint loading observed across the exercises tested in this study underscores the importance of implementing diverse exercise routines to optimize overall bone health and strengthen the musculoskeletal structure. Practitioners must therefore ensure that exercise programs include movements that are specifically suitable for their intended purpose.

ISTA Award 2023: Toward functional reconstruction of the pre-diseased state in total knee arthroplasty.

The surgical target for optimal implant positioning in robotic-assisted total knee arthroplasty remains the subject of ongoing discussion. One of the proposed targets is to recreate the knee's functional behaviour as per its pre-diseased state. The aim of this study was to optimize implant positioning, starting from mechanical alignment (MA), toward restoring the pre-diseased status, including ligament strain and kinematic patterns, in a patient population. We used an active appearance model-based approach to segment the preoperative CT of 21 osteoarthritic patients, which identified the osteophyte-free surfaces and estimated cartilage from the segmented bones; these geometries were used to construct patient-specific musculoskeletal models of the pre-diseased knee. Subsequently, implantations were simulated using the MA method, and a previously developed optimization technique was employed to find the optimal implant position that minimized the root mean square deviation between pre-diseased and postoperative ligament strains and kinematics. There were evident biomechanical differences between the simulated patient models, but also trends that appeared reproducible at the population level. Optimizing the implant position significantly reduced the maximum observed strain root mean square deviations within the cohort from 36.5% to below 5.3% for all but the anterolateral ligament; and concomitantly reduced the kinematic deviations from 3.8 mm (SD 1.7) and 4.7° (SD 1.9°) with MA to 2.7 mm (SD 1.4) and 3.7° (SD 1.9°) relative to the pre-diseased state. To achieve this, the femoral component consistently required translational adjustments in the anterior, lateral, and proximal directions, while the tibial component required a more posterior slope and varus rotation in most cases. These findings confirm that MA-induced biomechanical alterations relative to the pre-diseased state can be reduced by optimizing the implant position, and may have implications to further advance pre-planning in robotic-assisted surgery in order to restore pre-diseased knee function.

Effects of a soft back exoskeleton on lower lumbar spine loads during manual materials handling: a musculoskeletal modelling study

The aim of this study was to append a passive soft back exoskeleton to a validated musculoskeletal model and assess its effectiveness in reducing lumbar loads. Fifteen participants lifted a box, with and without wearing a CORFOR® exoskeleton. A full body OpenSim model was used to estimate lumbar joint moments and reaction forces, as well as low back muscles forces. Wearing the exoskeleton reduced the peak flexion moment, muscles forces, as well as peak compressive and shear forces. This musculoskeletal modelling study shows that wearing the exoskeleton may reduce lumbar spine loads and may contribute to prevent low back disorders.

Hamstrings are Stretched More and Faster during Accelerative Running Compared to Speed-Matched Constant-Speed Running.

Hamstring injuries are common in field-based sports and reinjury rates are high. Recent evidence suggests hamstring injuries often occur during accelerative running, but investigations of hamstring mechanics have primarily considered constant-speed running. Thus, our objective was to compare hamstring lengths and velocities between accelerative running and constant-speed running. We recorded videos of 10 participants during 6 accelerative running trials and 6 constant-speed running trials. We used OpenCap to estimate body segment kinematics and a 3-dimensional musculoskeletal model to compute peak length and step-average lengthening velocity of the biceps femoris (long head) muscle-tendon unit. We compared running conditions using linear mixed models with running speed as the independent variable. At running speeds below 75% of top speed, accelerative running resulted in greater peak lengths than constant-speed running. For example, the peak hamstring muscle-tendon length when a person accelerated from running at only 50% of top speed was equivalent to running at a constant 88% of top speed. Lengthening velocities were greater during accelerative running at all running speeds. Differences in hip flexion kinematics drove the greater peak lengths and lengthening velocities observed in accelerative running. Hamstrings are subjected to longer lengths and faster lengthening velocities in accelerative running than in constant-speed running. This provides a potential biomechanical perspective towards understanding the occurrence of hamstring injuries during acceleration. Our results suggest coaches and sports medicine staff should consider the accelerative nature of running in addition to running speed to quantify exposure to high-risk circumstances with long lengths and fast lengthening velocities of the hamstrings.

A generic detailed multibody model for simulating thoracic spine and ribcage kinematics

AbstractA reliable and comprehensive multibody musculoskeletal model of the thoracic spine and ribcage can offer valuable insight into the biomechanics of healthy and curved spines. In this study, we developed a generic rigid-body thoracic spine and ribcage model, which is kinematically determinate and controlled by spinal posture. A newly devised averaging constraint was implemented to model the kinematics of individual ribs and the sternum. Rib motion validation confirmed that the movement of adjacent ribs matched measured data across different tasks. We simulated 39 adolescent idiopathic scoliosis subjects aged 7–17 years, with an average (SD) Cobb angle of 15.9 (8.2) degrees. The average errors of multiple scoliosis metrics were less than 4 degrees for angle parameters, 5 mm for displacement parameters, and 3 percent for the ratio parameter. The model is straightforward and can simulate various daily activities (e.g., spinal articulation and breathing) while accurately capturing pathological deformities conforming to experimental data. It is available to the public on the open science platform Zenodo and will also be accessible through the AnyBody Managed Model Repository.

The Influence of Pelvic Tilt and Femoral Torsion on Hip Biomechanics: Implications for Clinical Assessment and Treatment

Background: Hip biomechanics are crucial in understanding movement disorders and joint pathologies. Pelvic tilt and femoral torsion are key factors influencing hip function and stability. This review aims to elucidate their effects on acetabular orientation, hip range of motion (ROM), and associated compensatory mechanisms. Methods: A comprehensive search of databases, including PubMed, Scopus, and Pedro, was conducted. Studies were selected based on Population, Concept, and Context (PCC) criteria, focusing on those examining the relationship between pelvic tilt, femoral torsion, and hip biomechanics. Eight studies were included, utilizing methodologies such as CT imaging, musculoskeletal modeling, and gait analysis, covering populations ranging from asymptomatic adults to elderly women with pelvic retroversion. Results: The review identified significant effects of pelvic retroversion on acetabular anteversion and hip extension. Some studies found no correlation between pelvic index (PI) and acetabular orientation, while others reported a linear increase in acetabular anteversion with pelvic retroversion. Subjects with pelvic retroversion showed greater hip extension. Additionally, femoral anteversion was linked to increased internal rotation and altered hip joint contact forces during gait, with changes in hip ROM and force distribution. No relationship was found between femoral and acetabular anteversion in patients with hip osteoarthritis. Conclusions: Pelvic tilt and femoral torsion significantly affect hip biomechanics, influencing acetabular orientation, ROM, and compensatory mechanisms. Future studies should include symptomatic populations to explore these relationships further. These findings emphasize the critical need for individualized clinical assessments and further research on symptomatic populations to enhance our understanding of pelvic tilt and femoral torsion’s impact on hip biomechanics.

Impact of Quadriceps Muscle Fatigue on Ankle Joint Compensation Strategies During Single-Leg Vertical Jump Landing.

This study investigates the impact of quadriceps fatigue on lower limb biomechanics during the landing phase of a single-leg vertical jump (SLJ) in 25 amateur male basketball players from Ningbo University. Fatigue was induced through single-leg knee flexion and extension exercises until task failure. Kinematic and dynamic data were collected pre-fatigue (PRF) and post-fatigue (POF) using the Vicon motion capture system and the AMTI force platform and analyzed using an OpenSim musculoskeletal model. Paired sample t-tests revealed significant changes in knee and hip biomechanics under different fatigue conditions, with knee joint angle (p < 0.001), velocity (p = 0.006), moment (p = 0.006), and power (p = 0.036) showing significant alterations. Hip joint angle (p = 0.002), moment (p = 0.033), and power (p < 0.001) also exhibited significant changes. Muscle activation and joint power were significantly higher in the POF condition, while joint stiffness was lower. These findings suggest that quadriceps fatigue leads to biomechanical adjustments in the knee and hip joints, which may increase the risk of injury despite aiding in landing stability.

Biomechanical significance of intervertebral discs on growthplate stresses in scoliotic trunks following unilateral muscle weakening: A hybrid approach of finite element and musculoskeletal modeling.

This study aimed to ascertain the relevance of intervertebral discs (IVD) in the stress distribution on growthplates (GPs) of a trunk model with adolescent idiopathic scoliosis (AIS) following a unilateral weakening of muscles. A thoracolumbar spine finite element (FE) model of a young female healthy and an AIS spine comprising GPs linked to the T12 through sacrum vertebrae. Two scenarios of including (FEI) and excluding (FEE) IVDs were considered. Then, using optimization-driven musculoskeletal models of the AIS and healthy trunks, the FE models were examined under subject-specific muscle forces and gravity loads. Results of this study demonstrate that when IVDs included in the FE model, an increase, ranging from 0.2 to 1.7 MPa, with the highest value occurring at the apex of the AIS model, in the von Mises stresses in the GPs. The ratio of 1.5 was found for the maximum von-Mises stress value on the most tilted GP in the FEI over the FEE model. Unilateral paralysis of muscles caused a reduction of 50% and 63% in the von Mises stress ratio of the concave-over-convex side of the most tilted GP in the FEI and FEE models of the AIS spine with healthy muscles, respectively. The intradiscal pressures, found for FEE and FEI models, assented to recent in-vivo investigations. Nonetheless, employing IVDs in the simulations provides an indispensable tool to anticipate the effects of neuromuscular disorders on GP stresses in an AIS spine and predict deformity progression during growth.

The impact of anterior knee displacement on knee joint load during the forward bow step in Tai Chi.

While the forward bow step is a crucial component of Tai Chi (TC) practice, little research has been conducted on its impact on knee joint load and muscle coordination. This study aims to investigate the effects of three different knee forward positions during the TC forward bow step on knee joint loading. Twenty TC practitioners were recruited, and motion capture systems, force platforms, and surface electromyography were utilized to synchronously collect biomechanical parameters of three types of forward bow steps: knee joint not exceeding the tip of the foot (NETT), knee joint forward movement level with the tip of the foot (LTT), and knee joint forward movement exceeding the tip of the foot (ETT). Ligament and muscle forces were calculated using OpenSim software for musculoskeletal modeling and simulation. One-way ANOVA was used to analyze the variations of the indicators during the peak anterior displacement of the knee joint in three movements. Additionally, spm1d one-way ANOVA was employed to examine the variations in the one-dimensional curve of the indicators throughout the entire movement process. Compared with LTT and ETT, the NETT posture was associated with significantly decreased knee flexion angle (F = 27.445, p = 0.001), knee anterior-posterior translation (F = 36.07, p < 0.001), flexion-extension torque (F = 22.232, p = 0.001), ligament force (F = 9.055, p = 0.011). Additionally, there was also a significant reduction in muscle strength, including quadriceps (F = 62.9, p < 0.001), long biceps femoris (F = 18.631, p = 0.002), lateral gastrocnemius (F = 24.933, p = 0.001) and soleus (F = 7.637, p = 0.017). This study further confirms that in the forward lunge movement of Tai Chi, the knee joint load is mainly concentrated during the forward movement phase. Compared to the knee joint load at the NETT position, the load is greater at the LTT position; and compared to the LTT position, the load is even greater at the ETT position.

Comparing on-line continuous movement decoding with joints unconstrained and constrained based on a generic musculoskeletal model.

Human-machine interface (HMI) has been extensively developed and applied in rehabilitation. However, the performance of amputees on continuous movement decoding was significantly decreased compared with that of able-bodied individuals. To explore the impact of the absence of joint movements on the performance of HMI in rehabilitation, a generic musculoskeletal model (MM) was employed in this study to evaluate and compare the performance of subjects completing a series of on-line tasks with the wrist and metacarpophalangeal (MCP) joints unconstrained and constrained. The performance of the generic MM has been demonstrated in previous studies. The electromyography (EMG) signals of four muscles were employed as inputs of the generic MM to realize the continuous movement decoding of wrist and MCP joints. Ten able-bodied subjects were recruited to perform the on-line tasks. The completion time, the number of overshoots, and the path efficiency of the tasks were taken as the indexes to quantify the subjects' performance. The muscle activation associated with the movement was analyzed. Across all tasks and subjects, the average values of the three indexes with the joints unconstrained were 7.7 s, 0.59, and 0.38, respectively, while those with the joints constrained were 17.86 s, 1.47, and 0.22, respectively. The results demonstrated that the subjects performed better with the wrist and MCP joints unconstrained than with those joints constrained in the on-line tasks, suggesting that the absence of joint movements can be a reason of the decreased performance of continuous movement decoding with HMIs. Meanwhile, it is revealed that the different performance on motion behaviors is caused by the absence of joint movements.

Neuro-Musculoskeletal Modeling for Online Estimation of Continuous Wrist Movements from Motor Unit Activities.

Decoding movement intentions from motor unit (MU) activities remains an ongoing challenge, which restricts our comprehension of the intricate transition mechanism from microscopic neural drive to macroscopic movements. This study presents an innovative neuro-musculoskeletal (NMS) model driven by MU activities for online estimation of continuous wrist movements. The proposed model employs a physiological and comprehensive utilization of MU firings and waveforms, thus facilitating the localization of MUs to muscle-tendon units (MTU) as well as the computation of MU-specific neural excitation. Subsequently, the MU-specific neural excitation was integrated to form the MTU-specific neural excitation, which were then inputted into a musculoskeletal model to accomplish the joint angle estimation. To assess the effectiveness of this model, high-density surface electromyography and angular data were collected from the forearms of eight subjects during their performance of wrist flexion-extension task. Two pieces of 8 × 8 electrode arrays and a motion capture system were employed for data acquisition. Following offline model calibration with a global optimization algorithm, online angle estimation results demonstrated a significant superiority of the proposed model over the state-of-the-art NMS models (p < 0.05), yielding the lowest normalized root mean square error (0.10 ± 0.02) and the highest determination coefficient (0.87 ± 0.06). This study provides a novel idea for the decoding of joint movements from MU activities. The research findings hold the potential to advance the development of NMS models towards the control of multiple degrees of freedom, with promising applications in the fields of motor control, biomechanics, and neuro-rehabilitation engineering.

Multibody dynamics-based musculoskeletal modeling for gait analysis: a systematic review.

Beyond qualitative assessment, gait analysis involves the quantitative evaluation of various parameters such as joint kinematics, spatiotemporal metrics, external forces, and muscle activation patterns and forces. Utilizing multibody dynamics-based musculoskeletal (MSK) modeling provides a time and cost-effective non-invasive tool for the prediction of internal joint and muscle forces. Recent advancements in the development of biofidelic MSK models have facilitated their integration into clinical decision-making processes, including quantitative diagnostics, functional assessment of prosthesis and implants, and devising data-driven gait rehabilitation protocols. Through an extensive search and meta-analysis of over 116 studies, this PRISMA-based systematic review provides a comprehensive overview of different existing multibody MSK modeling platforms, including generic templates, methods for personalization to individual subjects, and the solutions used to address statically indeterminate problems. Additionally, it summarizes post-processing techniques and the practical applications of MSK modeling tools. In the field of biomechanics, MSK modeling provides an indispensable tool for simulating and understanding human movement dynamics. However, limitations which remain elusive include the absence of MSK modeling templates based on female anatomy underscores the need for further advancements in this area.

A Machine Learning Approach for Predicting Pedaling Force Profile in Cycling

Accurate measurement of pedaling kinetics and kinematics is vital for optimizing rehabilitation, exercise training, and understanding musculoskeletal biomechanics. Pedal reaction force, the main external force in cycling, is essential for musculoskeletal modeling and closely correlates with lower-limb muscle activity and joint reaction forces. However, sensor instrumentation like 3-axis pedal force sensors is costly and requires extensive postprocessing. Recent advancements in machine learning (ML), particularly neural network (NN) models, provide promising solutions for kinetic analyses. In this study, an NN model was developed to predict radial and mediolateral forces, providing a low-cost solution to study pedaling biomechanics with stationary cycling ergometers. Fifteen healthy individuals performed a 2 min pedaling task at two different self-selected (58 ± 5 RPM) and higher (72 ± 7 RPM) cadences. Pedal forces were recorded using a 3-axis force system. The dataset included pedal force, crank angle, cadence, power, and participants’ weight and height. The NN model achieved an inter-subject normalized root mean square error (nRMSE) of 0.15 ± 0.02 and 0.26 ± 0.05 for radial and mediolateral forces at high cadence, respectively, and 0.20 ± 0.04 and 0.22 ± 0.04 at self-selected cadence. The NN model’s low computational time suits real-time pedal force predictions, matching the accuracy of previous ML algorithms for estimating ground reaction forces in gait.

Altering prosthetic alignment does not affect hip and low back joint loading during sit-to-stand in people with a transtibial amputation

People with a transtibial amputation (TTA) have greater prevalence of low back and hip joint pain compared to the general population. Altered movement, loading patterns, and neuromuscular activation during daily tasks like sit-to-stand likely contribute to these high rates of pain. In addition, muscle activation, ground reaction forces, and trunk range of motion can be affected by prosthetic alignment during sit-to-stand. However, it is unclear how prosthetic alignment affects joint contact forces during this task. The purpose of this study was to investigate the effect of prosthetic alignment on hip and low-back joint loading in people with TTA during sit-to-stand. Kinematics, ground reaction forces, and muscle activity data were collected from 10 people with TTA and 10 age- and sex- matched individuals without limb loss during five self-paced sit-to-stand trials. Participants with TTA completed the sit-to-stand task with their prescribed alignment and six altered alignment conditions (±10 mm anterior/posterior, medial/lateral, and ± 20 mm short/tall). A musculoskeletal model was used to calculate hip and L4-L5 joint loading. There were no differences in hip or L4-L5 joint loading between alignments. Participants with TTA had a greater peak hip joint contact force on the intact side hip compared to the amputated side hip across all alignments. Participants with TTA had greater L4-L5 joint contact force compared to those without amputation. While prosthetic alignment did not affect joint loading during sit-to-stand, future work on additional dynamic tasks is needed to better understand the potential role of prosthetic alignment on joint loading.

Assessment of mechanical variables best describing bone remodelling responses based on their correlation with bone density

Density distribution in bones can be estimated using bone remodelling models (BRM) and applying daily normal loads to assess the stress/strain state to which the bone is subjected. These models locally relate a certain mechanical stimulus, derived from the stress/strain state, directly to bone density or to its variation over time. The background of this idea is Frost’s Mechanostat Theory, which states that overloading states tend to increase bone density and disuse states tend to decrease it. Different variables have been proposed in the literature to measure the mechanical stimulus. Strain energy density (SED) and stresses have been commonly used as mechanical stimuli, but to date their use has not been justified with convincing arguments. In this paper we have selected several variables derived from stress and strain tensors and correlated them with the distribution of bone density in the femur of 13 elderly women to conclude which would be most appropriate for use as a mechanical stimulus in a BRM. We have performed this correlation analysis for six different activities: walking normally, fast walking, stair ascent, stair descent, rising from and sitting on a chair, and jumping in place. Musculoskeletal models were used to estimate joint reaction and muscle forces of each individual for each activity. These were applied to the corresponding finite element model of the femur to obtain stress and strain tensors at each point. The variables proposed as mechanical stimulus and derived from these tensors were correlated to the actual density obtained for each individual from CT-scans. Our results show that stress variables are the best correlated with density. In contrast, the correlations of SED are very weak, so it is not a good candidate for mechanical stimulus. Strains are also weakly correlated to density, but in this case because their distribution across the femur is rather uniform. This is in agreement with the Mechanostat Theory which states that bone reacts to load changes by changing its stiffness so to keep strains in a certain interval. Consequently, a plausible choice for a remodelling criterion could be keeping that strain uniformity.